5 Best Applications of Python in Data-driven Decision Making
Over the past few years, technologies are continuously changing worldwide. We are living an upgrading life than we ever imagined in our wildest dreams. But there are a few great people who not only dreamed but made it come true with continuous effort and consistency. They are tomorrow’s future and eminent data science personnel who change the world in multiple ways and set a new bar for living a better life.
Have you ever thought about what made these technologies so powerful and popular at the same time? It’s nothing but programming languages like Python and R and their libraries that simplify the whole technology with advanced algorithms.
Yes, you heard it right. Python is not a new language anymore, but its popularity keeps growing over the past few years due to data science, machine learning, and artificial intelligence.
Python’s Top-Notch Applications in Data-driven Decision Making
The world is too excited about data science and data-driven decision-making, and those who have a career in it have a rewarding career. Intelligent coding algorithms help us to understand the business inside out, in all aspects. Where we once had some raw data, but now we talk about complex data. Whether it’s a big or small enterprise, the world runs on data, and you need data to make any business sustain in this world.
Data analysis is overwhelming; the more you get into it, the better you know the business insights. But that is not what we are talking about, other than data-driven decision-making. So let’s learn about some of the best applications of Python in data-driven decision-making in detail.
Sometimes how well you know Python and its algorithms define how much you get out of it. This blog aims to make you understand the importance of Python in modern days technologies.
Web Development Using Python
You see the best animations, UI and UX when you type the website address and hit the keyboards’ enter key. Have you ever thought about what made it easy to develop such powerful and lightning-fast websites despite having so much content in them? Its Python that handles the content management system simplifies the web developers’ process using lazy images concept for faster loading.
The most popular web development frameworks are Flask, Django, Pyramid, Bottle, etc. And best CMS includes Django CMS, Wagtail, and Plone Content Management System. These advanced CMS platforms provide additional security, easy scalability in the development process using advanced protocols such as HTML, XML, FTP, etc. Python libraries not only enhance the functionalities of the web applications and help in developing them seamlessly.
Game Development Using Python
Python is not limited to website development anymore. It has already spread its mark in game development too. Have you heard about the famous games of the ’20? Then Battlefield 2.0 stands the tallest on the list for its popularity and flexibility.
If you are wondering about some of the great Python libraries for adding 2D and 3D graphics to your playing, then the set of libraries are PyGame, Pycap, Construct, Panda3D, PySoy, PyOpenGL. Their popularity due to Python is Sims 4, World of tanks, Eve Online, Disney Toontown, etc.
Artificial Intelligence and Machine Learning
Python programming is one of the top-most programming languages globally and most favorite for machine learning and artificial intelligence. The most creative brain behind most innovative technologies focuses on intelligent decision-making.
Python advanced libraries provide a handful of opportunities for developing ML and AI-powered solutions to machines. Since Python has opened many possibilities to the intellectual world, there is a steep rise in Python’s demand for data-driven decision-making.
Python has the most outstanding stability and top-notch security for handling intensive computations that help develop AI and ML systems runs smoothly. Python’s vast library collection facilitates developing new models and algorithms to integrate with modern technologies seamlessly.
Some of the prevalent Python libraries are SciPy, NumPy, Keras, Pandas, Tensor Flow, Scikit-learn.
Image and Text Processing
Have you ever come across a captcha that asks you to choose the right image, or types the right words that you read or hear for more security, or prove that you’re not a robot. And when you click or type the right words, you can download or open an account there. It’s on advanced ML, deep learning, and neural network algorithms (based on KNN Algorithms) that learn from themselves. For seamless functionalities, Python offers plenty of libraries that purely focus on image processing.
They are OpenCV, Scikit-image, Python Image Library (PIL). Some of the image processing platforms that use Python are GIMP, Corel Paintshop, Blender, Houdini, etc.
But text-processing is highly impossible with natural language processing (NLP). It allows handling an enormous amount of data by giving you the flexibility to arrange them as per your choice. You can use NLP to sort lines, extract texts, format paragraphs, and many more text processing things.
Data Visualizations Using Python
Data plays a crucial role in the modern world. It’s the customers’ critical understanding and their choices to create the right products for gathering and analyzing essential insights about them. The entire domain of data science revolves around; identifying problems, data gathering, analyzing and exploration, data analysis, and finally, data visualization for better understanding.
Python ecosystem offers various libraries that can help you solve critical problems and help in better decision-making to keep data science on the front line. Some real-time use Python libraries are TensorFlow, PyTorch, Pandas, Scikit-Learn, NumPy, SciPy, etc. helps in creating the best ML and deep learning models with data crunching and manipulations.
But not everyone understands this data without graphical representation, and to communicate with the stakeholders, you need data visualization. Python has multiple libraries for visual expression, including Plotly, Matplotlib, Seaborn, Ggplot, Geoplotlib as the most advanced data visualization tools.
Final Words
Python is the most popular programming language globally. It had many advanced libraries and enormous functionalities that helped in seamless integration and coped with modern technologies. In this blog, we learned about various Python libraries, their best use cases, and applications in data-driven decision-making.
